Caricature is an artistic drawing created to abstract or exaggerate facial features of a person. Rendering visually pleasing caricatures is a difficult task that requires professional skills, and thus it is of great interest to design a method to automatically generate such drawings. To deal with large shape changes, we propose an algorithm based on a semantic shape transform to produce diverse and plausible shape exaggerations. Specifically, we predict pixel-wise semantic correspondences and perform image warping on the input photo to achieve dense shape transformation. We show that the proposed framework is able to render visually pleasing shape exaggerations while maintaining their facial structures. In addition, our model allows users to manipulate the shape via the semantic map. We demonstrate the effectiveness of our approach on a large photograph-caricature benchmark dataset with comparisons to the state-of-the-art methods.

漫画是一种艺术绘画，旨在抽象或夸大一个人的面部特征。渲染视觉上令人愉悦的漫画是一项艰巨的任务，需要专业技能，因此设计一种自动生成此类图纸的方法非常有趣。为了处理大的形状变化，我们提出了一种基于语义形状变换的算法，以产生多样化和合理的形状夸张。具体来说，我们预测像素级语义对应关系并对输入照片执行图像变形以实现密集形状变换。我们表明，所提出的框架能够在保持面部结构的同时呈现视觉上令人愉悦的夸张形状。此外，我们的模型允许用户通过语义图来操纵形状。